Customers need to determine the amount of computing resources that are required to be utilized when deploying software. Typically, sales engineers interface with customers to define these required computing resources to meet various customer requirements, such as transaction throughput, scalability, high availability/disaster recovery and operational costs.
Software as a service (SaaS) is a software licensing and delivery model in which software is licensed on a subscription basis and is centrally hosted. Typically, SaaS products can be evaluated with minimal information and purchased by entering billing information. More advanced licenses, however, may have the customer contact the sales department directly so that they understand the unique needs and requirements of the customer, and provide offerings unique for the customer as a whole (e.g., multi-product enterprise license for X users with a negotiable contract term).
Many companies use a freemium model to lower the barrier for evaluating SaaS products. Freemium is a pricing strategy by which a product (e.g., software) is provided free of charge, but money (premium) is charged for additional features or services. The freemium model enables the software provider to provide limited service for free, and expand to small teams, small/medium business, or to full enterprise license contracts. Depending on the tier of service, the customer will gain access to more features, support, reliability or other variations for the specific product offering terms.
Currently, customers may use a third party or internal data to determine if their capacity needs (i.e., the amount of computing resources) of their use case (i.e., particular workload to be implemented) are adequate for the SaaS or software offering. These benchmarks provide rough estimates on the computational power required to meet the requirements of these use cases. Although the benchmarks may provide a good estimate for the upfront and operational costs, the unique customer use case will often under/over plan the capacity once the software is deployed into a live production environment.